A Real-World Evaluation of Frontline Treatment for Acute Myeloid Leukemia With Azacitidine Plus Venetoclax
Bibliographic record
Abstract
BACKGROUND: The combination of venetoclax + azacitidine (VenAza) has become the standard frontline treatment for older unfit AML patients. METHODS: We analyzed outcomes using VenAza for previously untreated unfit AML patients at a single center between 2020-2024. RESULTS: The overall response rate (ORR) was 69/105 (66%), was highest for patients with NPM1 (78%) and IDH1/2 (82%) mutations and lowest with TP53 mutations (40%). The median overall survival (OS) was 9.6 months, and 16.3 months for those achieving CR/CRi. There was no significant difference in OS between those achieving CR and CRi (p = 0.077). Patients treated between 2022-24 had a lower early death rate (8% vs. 22%) and better OS (median 10.4 vs 5.8 mos, p = 0.033) than those treated between 2020-21. There was no difference in OS between by age grouping or for patients with prior hypomethylating agent exposure. Patients with FLT3-ITD/RAS or TP53 mutations had an inferior OS compared with the other patients (median OS 8.1, 1.7 and 16 months, respectively). On multivariate analysis, achievement of CR/CRi was associated with better OS (p < 0.001), and FLT3-ITS/RAS/TP53 mutations were associated with inferior OS (p = 0.003), while ELN2022 risk group was not associated with OS. The median DFS for patients achieving CR/CRi was 7.1, 4.9 and 21 mos, for those with FLT3-ITD/RAS, TP53 and others, respectively (p = 0.003). CONCLUSIONS: This real-world analysis confirmed the prognostic importance of the mutational risk classification with VenAza treatment. OS was inferior to that reported in the VIALE A study but did improve over time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".